ask_agent_tool

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It adds useful context by explaining that the agent's instructions, knowledge, and tools live server-side, so the caller does not need to understand its internals. It does not mention potential latency, side effects, or authentication requirements, but for a straightforward ask-and-answer interaction this is acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: the core purpose is in the first sentence, followed by brief usage context and a clear exclusion. Every sentence adds value; there is no redundant or repeated information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with an output schema and few siblings, the description provides sufficient context: what it does, when to use it, how to phrase input, and when to avoid it. The explicit alternative and clear scope make it safe for an AI agent to select and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has only a `prompt` string with no description (0% coverage). The description compensates by instructing the agent to pass the user's request in plain language and clarifying that the agent handles the domain semantics. This adds meaningful guidance for the single parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the action ('Ask the Microsoft Foundry agent a question') and the result ('return its answer'). It also distinguishes itself from sibling tools by explicitly warning against using it for Power BI model reads, for which `inspect_model` is the appropriate alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It tells the agent when to use the tool ('anything the agent is specialised in') and how ('Pass the user's request in plain language'). It also provides an explicit exclusion: 'Do NOT use this to read a Power BI model' and names the better alternative, `inspect_model`.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.